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Runtime error
| import pandas as pd | |
| from PIL import Image | |
| import streamlit as st | |
| from streamlit_drawable_canvas import st_canvas | |
| from transformers import TrOCRProcessor, VisionEncoderDecoderModel | |
| processor = TrOCRProcessor.from_pretrained("UBC-NLP/ArOCR-Fonts-v2") | |
| model = VisionEncoderDecoderModel.from_pretrained("UBC-NLP/ArOCR-Fonts-v2") | |
| def predict(img): | |
| # if img is None: | |
| # _,generated_text=main(image) | |
| # return generated_text | |
| # else: | |
| images = Image.fromarray(img).convert("RGB") | |
| pixel_values = processor(images, return_tensors="pt").pixel_values | |
| # PIL_image = Image.fromarray(np.uint8(pixel_values.squeeze()[0,:,:])).convert('RGB') | |
| generated_ids = model.generate(pixel_values,max_length=512) | |
| generated_text = processor.batch_decode( | |
| generated_ids, skip_special_tokens=True)[0] | |
| return generated_text | |
| # Specify canvas parameters in application | |
| stroke_width = st.sidebar.slider("Stroke width: ", 1, 25, 3) | |
| stroke_color = st.sidebar.color_picker("Stroke color hex: ") | |
| bg_color = st.sidebar.color_picker("Background color hex: ", "#eee") | |
| bg_image = st.sidebar.file_uploader("Background image:", type=["png", "jpg"]) | |
| realtime_update = st.sidebar.checkbox("Update in realtime", True) | |
| # Create a canvas component | |
| canvas_result = st_canvas( | |
| fill_color="rgba(255, 165, 0, 0.3)", # Fixed fill color with some opacity | |
| stroke_width=stroke_width, | |
| stroke_color=stroke_color, | |
| background_color=bg_color, | |
| background_image=Image.open(bg_image) if bg_image else None, | |
| update_streamlit=realtime_update, | |
| height=200, | |
| drawing_mode="freedraw", | |
| display_toolbar=st.sidebar.checkbox("Display toolbar", True), | |
| key="full_app", | |
| ) | |
| # Do something interesting with the image data and paths | |
| if canvas_result.image_data is not None: | |
| st.image(canvas_result.image_data) | |
| st.text(predict(canvas_result.image_data)) |